NuSVC
#include <Skigen/SVM>
template <typename Scalar = double>
class Skigen::NuSVC(nu=0.5, kernel=Kernel::RBF, degree=3, gamma=0, coef0=0, tol=1e-3, max_passes=50, random_state=std::nullopt)
Nu-Support Vector Classification with kernels.
Solves the nu-SVM binary classification dual via a dedicated SMO variant. The nu parameter is an upper bound on the fraction of margin errors and a lower bound on the fraction of support vectors.
Mirrors the dense binary core of sklearn.svm.NuSVC.
Attributes:
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nu : Scalar
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kernel : Kernel
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classes : const Eigen::VectorXi
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support : const std::vector< Eigen::Index > &
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n_support : int
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intercept : Scalar
Methods
SKIGEN_PARAMS()
predict(X)
decision_function(X)
Raw decision function — sum_s dual_coef_s K(x, sv_s) + b.